Improving Human fMRI through Modeling and Imaging Microvascular Dynamics: Administrative Supplement
Improving Human fMRI through Modeling and Imaging Microvascular Dynamics: Administrative Supplement
批准号:
10179989
负责人:
Jonathan Rizzo Polimeni
金额:
$17.08万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-09-15 至 2022-07-31
关键词:
Administrative SupplementAnatomyAngiographyArchitectureBeliefBloodBlood VesselsBlood capillariesBlood flowBrainBrain MappingCaliberCerebral cortexContractsDataDevelopmentFormulationFunctional Magnetic Resonance ImagingFutureHumanImageImaging TechniquesKnowledgeLinkMagnetic Resonance ImagingMapsMeasuresModelingNeuronsPopulationProceduresPsyche structureResolutionRodentSignal TransductionSpecificitySpecimenTechniquesTechnologyTestingTreesValidationVisual Cortexarea striataarteriolebasecerebral blood volumehemodynamicsimprovedin vivooptical imagingreconstructionresponsespatiotemporaltwo photon microscopyvenule
中文摘要
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英文摘要
PROJECT SUMMARY/ABSTRACT
All fMRI signals have a vascular origin, and this has been believed to be a major limitation to precise
spatiotemporal localization of neuronal activation when using hemodynamic functional contrast such as BOLD.
However, significant recent discoveries made using powerful ultrahigh-resolution optical imaging techniques
have challenged this belief. Unfortunately these measures require invasive procedures and therefore cannot
be performed in humans. Our aim is to transfer knowledge gained from these invasive studies into interpreting
human fMRI data in order to help fMRI reach its full potential. In this proposal we plan to combine detailed
maps of human macro- and meso-scale vasculature measured with high-resolution MRI with maps of the
micro-scale vasculature measured in human brain specimens with CLARITY-assisted microimaging. We will
then link this anatomical information with dynamic models built from 2-photon microscopy performed in rodents
where the changes in vessel diameter, blood flow and oxygenation can be measured directly in each vessel
type across all stages of the vascular hierarchy. We hypothesize that newly introduced models of hemo- and
vaso-dynamics built from 2-photon microscopy, linked with a detailed micro- and macroscopically mapped
human microvascular anatomy, can be exploited to improve the spatial and temporal specificity of human fMRI.
To supply human vasculature reconstructions to our models, we propose a two-scale approach. We first
advance 7 Tesla MR Angiography (MRA) techniques to image the pial vascular network as well as intracortical
vessels and vascular layers of the cerebral cortex to achieve a mesoscopic model. To form the micron-scale
model of vasculature at the capillary level, we will use the CLARITY technique to image the full vascular tree
(from arterioles through capillaries to venules) in human primary visual cortex.
To predict vasodynamic changes driven by neuronal activation, we will adapt a model derived from
dynamic in vivo 2-photon microscopy of vessel diameters in rodents to human microvascular anatomy. To
adapt this to human microvasculature requires a careful multi-stage transferal. First we will measure bulk
changes in microvessel diameter, a.k.a. cerebral blood volume (CBV), across multiple levels of the vascular
hierarchy and confirm that the model can predict the CBV-fMRI signal. The CBV-fMRI signal is used because it
is a vasodynamic signal directly reflecting vessel diameter changes occurring alongside local neuronal activity
(rather than the subsequent hemodynamic changes). After performing this validation we will build a dynamic
model of the microvascular tree in human cortex based on our vascular reconstruction, and again measure
CBV-fMRI changes across multiple levels of the vascular hierarchy. We will finally test the ability of this model
to improve the neuronal specificity of fMRI by imaging the functional architecture in human visual cortex. This
model will also enable the formulation and testing of hypotheses about the discriminability of fMRI responses
elicited from nearby neuronal populations, and guide development of future advanced acquisition technologies.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
Towards Optimising MRI Characterisation of Tissue (TOMCAT) Dataset including all Longitudinal Automatic Segmentation of Hippocampal Subfields (LASHiS) data.
优化组织 MRI 表征 (TOMCAT) 数据集,包括所有海马子域纵向自动分割 (LASHiS) 数据。
DOI:
10.1016/j.dib.2020.106043
发表时间:
2020
期刊:
Data in brief
影响因子:
1.2
作者:
[Shaw,ThomasB, York,Ashley, Barth,Markus, Bollmann,Steffen]
通讯作者:
Bollmann,Steffen
DOI:
10.1016/j.pneurobio.2020.101936
发表时间:
2021-12
期刊:
Progress in neurobiology
影响因子:
6.7
作者:
[Bollmann S, Barth M]
通讯作者:
Barth M
DOI:
10.1002/hbm.26094
发表时间:
2023-02-01
期刊:
Human brain mapping
影响因子:
4.8
作者:
[]
通讯作者:
High-Performance Gradient Coil for 7 Tesla MRI
-
批准号:10630533
-
项目类别:
-
资助金额:$200.0万
-
财政年份:2023
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
fMRI Technologies for Imaging at the Limit of Biological Spatiotemporal Resolution: Administrative Supplement
-
批准号:10833383
-
项目类别:
-
资助金额:$4.55万
-
财政年份:2023
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
CRCNS: Computational Modeling of Microvascular Effects in Cortical Laminar fMRI
-
批准号:10643880
-
项目类别:
-
资助金额:$20.93万
-
财政年份:2021
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
CRCNS: Computational Modeling of Microvascular Effects in Cortical Laminar fMRI
-
批准号:10482354
-
项目类别:
-
资助金额:$16.73万
-
财政年份:2021
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
CRCNS: Computational Modeling of Microvascular Effects in Cortical Laminar fMRI
-
批准号:10398277
-
项目类别:
-
资助金额:$17.4万
-
财政年份:2021
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Improving Human fMRI through Modeling and Imaging Microvascular Dynamics
-
批准号:9753356
-
项目类别:
-
资助金额:$93.42万
-
财政年份:2016
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Improving Human fMRI through Modeling and Imaging Microvascular Dynamics
-
批准号:9205860
-
项目类别:
-
资助金额:$96.56万
-
财政年份:2016
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Improving Human fMRI through Modeling and Imaging Microvascular Dynamics
-
批准号:9974595
-
项目类别:
-
资助金额:$93.0万
-
财政年份:2016
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Fast MRI at the Limit of Biological Temporal Resolution
-
批准号:9428443
-
项目类别:
-
资助金额:$60.2万
-
财政年份:2015
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
fMRI Technologies for Imaging at the Limit of Biological Spatiotemporal Resolution
-
批准号:10382317
-
项目类别:
-
资助金额:$73.51万
-
财政年份:2015
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
fMRI Technologies for Imaging at the Limit of Biological Spatiotemporal Resolution
-
批准号:10188527
-
项目类别:
-
资助金额:$74.24万
-
财政年份:2015
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Fast MRI at the Limit of Biological Temporal Resolution
-
批准号:8909408
-
项目类别:
-
资助金额:$61.35万
-
财政年份:2015
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Fast MRI at the Limit of Biological Temporal Resolution
-
批准号:9224993
-
项目类别:
-
资助金额:$60.2万
-
财政年份:2015
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Biological Spatial Resolution Limits in fMRI
-
批准号:8044958
-
项目类别:
-
资助金额:$17.54万
-
财政年份:2011
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Biological Spatial Resolution Limits in fMRI
-
批准号:8440820
-
项目类别:
-
资助金额:$17.54万
-
财政年份:2011
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Biological Spatial Resolution Limits in fMRI
-
批准号:8240986
-
项目类别:
-
资助金额:$17.54万
-
财政年份:2011
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
Biological Spatial Resolution Limits in fMRI
-
批准号:8633457
-
项目类别:
-
资助金额:$17.54万
-
财政年份:2011
-
负责人:Jonathan Rizzo Polimeni
-
依托单位:
海外基金